Graph databases shine when the connections between data objects are as important as the objects themselves.
A social network is a classic example. User profiles are the primary objects - but the connections between them - who's friends with who - is just as important to creating the user experience.
Another example is one from academic research: citation graphs. Research papers reference other papers. If one was building an app to mine citation data, a graph database would be ideal.
I built a graph-based recommendation system by defining connections between parent/child/related products. I then was able to traverse the graph, starting at known purchased, and branching outward to find other products/services the customer may be interested in.
Cool.
We have been working on using graphdb in food industry trying to figure out a way to deliver value from this technology. I think it is more important to focus on the problem vs the tool. But the tool itself sometimes can change perspective.
I also came across this article on how graph theory is being used in Genomic. Fascinating! http://www.technologyreview.com/news/537916/rebooting-the-hu...
A social network is a classic example. User profiles are the primary objects - but the connections between them - who's friends with who - is just as important to creating the user experience.
Another example is one from academic research: citation graphs. Research papers reference other papers. If one was building an app to mine citation data, a graph database would be ideal.
I built a graph-based recommendation system by defining connections between parent/child/related products. I then was able to traverse the graph, starting at known purchased, and branching outward to find other products/services the customer may be interested in.